Overview

Dataset statistics

Number of variables24
Number of observations128975
Missing cells210495
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.8 MiB
Average record size in memory185.0 B

Variable types

Numeric4
Text7
DateTime1
Categorical10
Boolean2

Alerts

currency has constant value ""Constant
ship-country has constant value ""Constant
fulfilled-by has constant value ""Constant
Unnamed: 22 has constant value ""Constant
Status is highly imbalanced (58.3%)Imbalance
Sales Channel is highly imbalanced (98.9%)Imbalance
Courier Status is highly imbalanced (63.2%)Imbalance
B2B is highly imbalanced (94.2%)Imbalance
Courier Status has 6872 (5.3%) missing valuesMissing
currency has 7795 (6.0%) missing valuesMissing
Amount has 7795 (6.0%) missing valuesMissing
promotion-ids has 49153 (38.1%) missing valuesMissing
fulfilled-by has 89698 (69.5%) missing valuesMissing
Unnamed: 22 has 49050 (38.0%) missing valuesMissing
df_index is uniformly distributedUniform
df_index has unique valuesUnique
Qty has 12807 (9.9%) zerosZeros
Amount has 2343 (1.8%) zerosZeros

Reproduction

Analysis started2024-03-15 14:13:19.918719
Analysis finished2024-03-15 14:13:37.591335
Duration17.67 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

df_index
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct128975
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64487
Minimum0
Maximum128974
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:37.901165image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6448.7
Q132243.5
median64487
Q396730.5
95-th percentile122525.3
Maximum128974
Range128974
Interquartile range (IQR)64487

Descriptive statistics

Standard deviation37232.02
Coefficient of variation (CV)0.57735698
Kurtosis-1.2
Mean64487
Median Absolute Deviation (MAD)32244
Skewness0
Sum8.3172108 × 109
Variance1.3862233 × 109
MonotonicityStrictly increasing
2024-03-15T19:43:38.176298image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
85979 1
 
< 0.1%
85992 1
 
< 0.1%
85991 1
 
< 0.1%
85990 1
 
< 0.1%
85989 1
 
< 0.1%
85988 1
 
< 0.1%
85987 1
 
< 0.1%
85986 1
 
< 0.1%
85985 1
 
< 0.1%
Other values (128965) 128965
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
128974 1
< 0.1%
128973 1
< 0.1%
128972 1
< 0.1%
128971 1
< 0.1%
128970 1
< 0.1%
128969 1
< 0.1%
128968 1
< 0.1%
128967 1
< 0.1%
128966 1
< 0.1%
128965 1
< 0.1%
Distinct120378
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:38.583610image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters2450525
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113532 ?
Unique (%)88.0%

Sample

1st row405-8078784-5731545
2nd row171-9198151-1101146
3rd row404-0687676-7273146
4th row403-9615377-8133951
5th row407-1069790-7240320
ValueCountFrequency (%)
171-5057375-2831560 12
 
< 0.1%
403-4984515-8861958 12
 
< 0.1%
403-0173977-3041148 11
 
< 0.1%
404-9932919-6662730 11
 
< 0.1%
408-3317403-1729937 10
 
< 0.1%
406-9002076-4152331 9
 
< 0.1%
404-3701762-8241125 9
 
< 0.1%
171-4310662-2005103 9
 
< 0.1%
408-2964501-8373155 9
 
< 0.1%
171-0706521-2133101 9
 
< 0.1%
Other values (120368) 128874
99.9%
2024-03-15T19:43:39.185167image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 298773
12.2%
0 284703
11.6%
- 257950
10.5%
1 233906
9.5%
3 217114
8.9%
5 216718
8.8%
7 214101
8.7%
2 187121
7.6%
6 186690
7.6%
9 182039
7.4%
Other values (2) 171410
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2192451
89.5%
Dash Punctuation 257950
 
10.5%
Uppercase Letter 124
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 298773
13.6%
0 284703
13.0%
1 233906
10.7%
3 217114
9.9%
5 216718
9.9%
7 214101
9.8%
2 187121
8.5%
6 186690
8.5%
9 182039
8.3%
8 171286
7.8%
Dash Punctuation
ValueCountFrequency (%)
- 257950
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2450401
> 99.9%
Latin 124
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 298773
12.2%
0 284703
11.6%
- 257950
10.5%
1 233906
9.5%
3 217114
8.9%
5 216718
8.8%
7 214101
8.7%
2 187121
7.6%
6 186690
7.6%
9 182039
7.4%
Latin
ValueCountFrequency (%)
S 124
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2450525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 298773
12.2%
0 284703
11.6%
- 257950
10.5%
1 233906
9.5%
3 217114
8.9%
5 216718
8.8%
7 214101
8.7%
2 187121
7.6%
6 186690
7.6%
9 182039
7.4%
Other values (2) 171410
7.0%

Date
Date

Distinct91
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
Minimum2022-03-31 00:00:00
Maximum2022-06-29 00:00:00
2024-03-15T19:43:39.530757image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:39.846905image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Status
Categorical

IMBALANCE 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
Shipped
77804 
Shipped - Delivered to Buyer
28769 
Cancelled
18332 
Shipped - Returned to Seller
 
1953
Shipped - Picked Up
 
973
Other values (8)
 
1144

Length

Max length29
Median length7
Mean length12.457391
Min length7

Characters and Unicode

Total characters1606692
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowCancelled
2nd rowShipped - Delivered to Buyer
3rd rowShipped
4th rowCancelled
5th rowShipped

Common Values

ValueCountFrequency (%)
Shipped 77804
60.3%
Shipped - Delivered to Buyer 28769
 
22.3%
Cancelled 18332
 
14.2%
Shipped - Returned to Seller 1953
 
1.5%
Shipped - Picked Up 973
 
0.8%
Pending 658
 
0.5%
Pending - Waiting for Pick Up 281
 
0.2%
Shipped - Returning to Seller 145
 
0.1%
Shipped - Out for Delivery 35
 
< 0.1%
Shipped - Rejected by Buyer 11
 
< 0.1%
Other values (3) 14
 
< 0.1%

Length

2024-03-15T19:43:40.184987image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
shipped 109696
42.7%
32173
 
12.5%
to 30867
 
12.0%
buyer 28780
 
11.2%
delivered 28769
 
11.2%
cancelled 18332
 
7.1%
seller 2098
 
0.8%
returned 1953
 
0.8%
up 1254
 
0.5%
picked 973
 
0.4%
Other values (14) 2078
 
0.8%

Most occurring characters

ValueCountFrequency (%)
e 271710
16.9%
p 220662
13.7%
d 160674
10.0%
i 141426
8.8%
127998
8.0%
S 111802
 
7.0%
h 109704
 
6.8%
l 69664
 
4.3%
r 62101
 
3.9%
t 33302
 
2.1%
Other values (25) 297649
18.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1252920
78.0%
Uppercase Letter 193601
 
12.0%
Space Separator 127998
 
8.0%
Dash Punctuation 32173
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 271710
21.7%
p 220662
17.6%
d 160674
12.8%
i 141426
11.3%
h 109704
8.8%
l 69664
 
5.6%
r 62101
 
5.0%
t 33302
 
2.7%
o 31188
 
2.5%
u 30913
 
2.5%
Other values (12) 121576
9.7%
Uppercase Letter
ValueCountFrequency (%)
S 111802
57.7%
D 28805
 
14.9%
B 28780
 
14.9%
C 18332
 
9.5%
P 2193
 
1.1%
R 2109
 
1.1%
U 1254
 
0.6%
W 281
 
0.1%
O 35
 
< 0.1%
L 5
 
< 0.1%
Space Separator
ValueCountFrequency (%)
127998
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1446521
90.0%
Common 160171
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 271710
18.8%
p 220662
15.3%
d 160674
11.1%
i 141426
9.8%
S 111802
7.7%
h 109704
7.6%
l 69664
 
4.8%
r 62101
 
4.3%
t 33302
 
2.3%
o 31188
 
2.2%
Other values (23) 234288
16.2%
Common
ValueCountFrequency (%)
127998
79.9%
- 32173
 
20.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1606692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 271710
16.9%
p 220662
13.7%
d 160674
10.0%
i 141426
8.8%
127998
8.0%
S 111802
 
7.0%
h 109704
 
6.8%
l 69664
 
4.3%
r 62101
 
3.9%
t 33302
 
2.1%
Other values (25) 297649
18.5%

Fulfilment
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
Amazon
89698 
Merchant
39277 

Length

Max length8
Median length6
Mean length6.6090638
Min length6

Characters and Unicode

Total characters852404
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMerchant
2nd rowMerchant
3rd rowAmazon
4th rowMerchant
5th rowAmazon

Common Values

ValueCountFrequency (%)
Amazon 89698
69.5%
Merchant 39277
30.5%

Length

2024-03-15T19:43:40.400489image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:40.613330image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
amazon 89698
69.5%
merchant 39277
30.5%

Most occurring characters

ValueCountFrequency (%)
a 128975
15.1%
n 128975
15.1%
A 89698
10.5%
m 89698
10.5%
z 89698
10.5%
o 89698
10.5%
M 39277
 
4.6%
e 39277
 
4.6%
r 39277
 
4.6%
c 39277
 
4.6%
Other values (2) 78554
9.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 723429
84.9%
Uppercase Letter 128975
 
15.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 128975
17.8%
n 128975
17.8%
m 89698
12.4%
z 89698
12.4%
o 89698
12.4%
e 39277
 
5.4%
r 39277
 
5.4%
c 39277
 
5.4%
h 39277
 
5.4%
t 39277
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 89698
69.5%
M 39277
30.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 852404
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 128975
15.1%
n 128975
15.1%
A 89698
10.5%
m 89698
10.5%
z 89698
10.5%
o 89698
10.5%
M 39277
 
4.6%
e 39277
 
4.6%
r 39277
 
4.6%
c 39277
 
4.6%
Other values (2) 78554
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 852404
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 128975
15.1%
n 128975
15.1%
A 89698
10.5%
m 89698
10.5%
z 89698
10.5%
o 89698
10.5%
M 39277
 
4.6%
e 39277
 
4.6%
r 39277
 
4.6%
c 39277
 
4.6%
Other values (2) 78554
9.2%

Sales Channel
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
Amazon.in
128851 
Non-Amazon
 
124

Length

Max length10
Median length9
Mean length9.0009614
Min length9

Characters and Unicode

Total characters1160899
Distinct characters10
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmazon.in
2nd rowAmazon.in
3rd rowAmazon.in
4th rowAmazon.in
5th rowAmazon.in

Common Values

ValueCountFrequency (%)
Amazon.in 128851
99.9%
Non-Amazon 124
 
0.1%

Length

2024-03-15T19:43:40.948627image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:41.127597image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
amazon.in 128851
99.9%
non-amazon 124
 
0.1%

Most occurring characters

ValueCountFrequency (%)
n 257950
22.2%
o 129099
11.1%
A 128975
11.1%
m 128975
11.1%
a 128975
11.1%
z 128975
11.1%
. 128851
11.1%
i 128851
11.1%
N 124
 
< 0.1%
- 124
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 902825
77.8%
Uppercase Letter 129099
 
11.1%
Other Punctuation 128851
 
11.1%
Dash Punctuation 124
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 257950
28.6%
o 129099
14.3%
m 128975
14.3%
a 128975
14.3%
z 128975
14.3%
i 128851
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 128975
99.9%
N 124
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 128851
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1031924
88.9%
Common 128975
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 257950
25.0%
o 129099
12.5%
A 128975
12.5%
m 128975
12.5%
a 128975
12.5%
z 128975
12.5%
i 128851
12.5%
N 124
 
< 0.1%
Common
ValueCountFrequency (%)
. 128851
99.9%
- 124
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1160899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 257950
22.2%
o 129099
11.1%
A 128975
11.1%
m 128975
11.1%
a 128975
11.1%
z 128975
11.1%
. 128851
11.1%
i 128851
11.1%
N 124
 
< 0.1%
- 124
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
Expedited
88615 
Standard
40360 

Length

Max length9
Median length9
Mean length8.6870711
Min length8

Characters and Unicode

Total characters1120415
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStandard
2nd rowStandard
3rd rowExpedited
4th rowStandard
5th rowExpedited

Common Values

ValueCountFrequency (%)
Expedited 88615
68.7%
Standard 40360
31.3%

Length

2024-03-15T19:43:41.313699image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:41.480861image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
expedited 88615
68.7%
standard 40360
31.3%

Most occurring characters

ValueCountFrequency (%)
d 257950
23.0%
e 177230
15.8%
t 128975
11.5%
E 88615
 
7.9%
x 88615
 
7.9%
p 88615
 
7.9%
i 88615
 
7.9%
a 80720
 
7.2%
S 40360
 
3.6%
n 40360
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 991440
88.5%
Uppercase Letter 128975
 
11.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 257950
26.0%
e 177230
17.9%
t 128975
13.0%
x 88615
 
8.9%
p 88615
 
8.9%
i 88615
 
8.9%
a 80720
 
8.1%
n 40360
 
4.1%
r 40360
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
E 88615
68.7%
S 40360
31.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 1120415
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 257950
23.0%
e 177230
15.8%
t 128975
11.5%
E 88615
 
7.9%
x 88615
 
7.9%
p 88615
 
7.9%
i 88615
 
7.9%
a 80720
 
7.2%
S 40360
 
3.6%
n 40360
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1120415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 257950
23.0%
e 177230
15.8%
t 128975
11.5%
E 88615
 
7.9%
x 88615
 
7.9%
p 88615
 
7.9%
i 88615
 
7.9%
a 80720
 
7.2%
S 40360
 
3.6%
n 40360
 
3.6%

Style
Text

Distinct1377
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:41.880478image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.2124675
Min length5

Characters and Unicode

Total characters801253
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)0.1%

Sample

1st rowSET389
2nd rowJNE3781
3rd rowJNE3371
4th rowJ0341
5th rowJNE3671
ValueCountFrequency (%)
jne3797 4224
 
3.3%
jne3405 2263
 
1.8%
j0230 1868
 
1.4%
set268 1860
 
1.4%
j0341 1630
 
1.3%
j0003 1627
 
1.3%
set324 1284
 
1.0%
set345 1250
 
1.0%
jne3373 1173
 
0.9%
jne3440 1054
 
0.8%
Other values (1367) 110742
85.9%
2024-03-15T19:43:42.503248image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 112713
14.1%
E 94474
11.8%
J 86819
10.8%
0 82160
10.3%
N 62119
 
7.8%
1 40872
 
5.1%
2 40109
 
5.0%
4 39852
 
5.0%
7 38572
 
4.8%
T 35079
 
4.4%
Other values (15) 168484
21.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 477803
59.6%
Uppercase Letter 323450
40.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 94474
29.2%
J 86819
26.8%
N 62119
19.2%
T 35079
 
10.8%
S 34901
 
10.8%
M 4360
 
1.3%
W 2317
 
0.7%
P 1718
 
0.5%
B 767
 
0.2%
L 451
 
0.1%
Other values (5) 445
 
0.1%
Decimal Number
ValueCountFrequency (%)
3 112713
23.6%
0 82160
17.2%
1 40872
 
8.6%
2 40109
 
8.4%
4 39852
 
8.3%
7 38572
 
8.1%
8 32460
 
6.8%
9 31415
 
6.6%
5 30087
 
6.3%
6 29563
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 477803
59.6%
Latin 323450
40.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 94474
29.2%
J 86819
26.8%
N 62119
19.2%
T 35079
 
10.8%
S 34901
 
10.8%
M 4360
 
1.3%
W 2317
 
0.7%
P 1718
 
0.5%
B 767
 
0.2%
L 451
 
0.1%
Other values (5) 445
 
0.1%
Common
ValueCountFrequency (%)
3 112713
23.6%
0 82160
17.2%
1 40872
 
8.6%
2 40109
 
8.4%
4 39852
 
8.3%
7 38572
 
8.1%
8 32460
 
6.8%
9 31415
 
6.6%
5 30087
 
6.3%
6 29563
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 801253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 112713
14.1%
E 94474
11.8%
J 86819
10.8%
0 82160
10.3%
N 62119
 
7.8%
1 40872
 
5.1%
2 40109
 
5.0%
4 39852
 
5.0%
7 38572
 
4.8%
T 35079
 
4.4%
Other values (15) 168484
21.0%

SKU
Text

Distinct7195
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:42.847969image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length29
Median length27
Mean length13.363807
Min length6

Characters and Unicode

Total characters1723597
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique893 ?
Unique (%)0.7%

Sample

1st rowSET389-KR-NP-S
2nd rowJNE3781-KR-XXXL
3rd rowJNE3371-KR-XL
4th rowJ0341-DR-L
5th rowJNE3671-TU-XXXL
ValueCountFrequency (%)
jne3797-kr-l 773
 
0.6%
jne3797-kr-m 657
 
0.5%
jne3797-kr-s 587
 
0.5%
jne3405-kr-l 535
 
0.4%
j0230-skd-m 507
 
0.4%
jne3797-kr-xl 474
 
0.4%
j0230-skd-s 452
 
0.4%
jne3405-kr-s 443
 
0.3%
jne3797-kr-xs 431
 
0.3%
jne3797-kr-xxl 395
 
0.3%
Other values (7186) 123887
95.9%
2024-03-15T19:43:43.631521image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 305956
17.8%
3 114980
 
6.7%
X 114392
 
6.6%
R 101927
 
5.9%
E 99609
 
5.8%
K 99485
 
5.8%
N 90548
 
5.3%
J 88172
 
5.1%
0 83775
 
4.9%
L 79565
 
4.6%
Other values (26) 545188
31.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 924270
53.6%
Decimal Number 493039
28.6%
Dash Punctuation 305956
 
17.8%
Space Separator 332
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
X 114392
12.4%
R 101927
11.0%
E 99609
10.8%
K 99485
10.8%
N 90548
9.8%
J 88172
9.5%
L 79565
8.6%
S 78899
8.5%
T 54737
5.9%
P 53213
5.8%
Other values (14) 63723
6.9%
Decimal Number
ValueCountFrequency (%)
3 114980
23.3%
0 83775
17.0%
1 43978
 
8.9%
4 41363
 
8.4%
2 40957
 
8.3%
7 39908
 
8.1%
8 33423
 
6.8%
5 32287
 
6.5%
9 31775
 
6.4%
6 30593
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 305956
100.0%
Space Separator
ValueCountFrequency (%)
332
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 924270
53.6%
Common 799327
46.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
X 114392
12.4%
R 101927
11.0%
E 99609
10.8%
K 99485
10.8%
N 90548
9.8%
J 88172
9.5%
L 79565
8.6%
S 78899
8.5%
T 54737
5.9%
P 53213
5.8%
Other values (14) 63723
6.9%
Common
ValueCountFrequency (%)
- 305956
38.3%
3 114980
 
14.4%
0 83775
 
10.5%
1 43978
 
5.5%
4 41363
 
5.2%
2 40957
 
5.1%
7 39908
 
5.0%
8 33423
 
4.2%
5 32287
 
4.0%
9 31775
 
4.0%
Other values (2) 30925
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1723597
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 305956
17.8%
3 114980
 
6.7%
X 114392
 
6.6%
R 101927
 
5.9%
E 99609
 
5.8%
K 99485
 
5.8%
N 90548
 
5.3%
J 88172
 
5.1%
0 83775
 
4.9%
L 79565
 
4.6%
Other values (26) 545188
31.6%

Category
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
Set
50284 
kurta
49877 
Western Dress
15500 
Top
10622 
Ethnic Dress
 
1159
Other values (4)
 
1533

Length

Max length13
Median length12
Mean length5.0905059
Min length3

Characters and Unicode

Total characters656548
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSet
2nd rowkurta
3rd rowkurta
4th rowWestern Dress
5th rowTop

Common Values

ValueCountFrequency (%)
Set 50284
39.0%
kurta 49877
38.7%
Western Dress 15500
 
12.0%
Top 10622
 
8.2%
Ethnic Dress 1159
 
0.9%
Blouse 926
 
0.7%
Bottom 440
 
0.3%
Saree 164
 
0.1%
Dupatta 3
 
< 0.1%

Length

2024-03-15T19:43:43.891454image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:44.114804image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
set 50284
34.5%
kurta 49877
34.2%
dress 16659
 
11.4%
western 15500
 
10.6%
top 10622
 
7.3%
ethnic 1159
 
0.8%
blouse 926
 
0.6%
bottom 440
 
0.3%
saree 164
 
0.1%
dupatta 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
t 117706
17.9%
e 99197
15.1%
r 82200
12.5%
u 50806
7.7%
S 50448
7.7%
a 50047
7.6%
k 49877
7.6%
s 49744
7.6%
D 16662
 
2.5%
n 16659
 
2.5%
Other values (12) 73202
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 544132
82.9%
Uppercase Letter 95757
 
14.6%
Space Separator 16659
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 117706
21.6%
e 99197
18.2%
r 82200
15.1%
u 50806
9.3%
a 50047
9.2%
k 49877
9.2%
s 49744
9.1%
n 16659
 
3.1%
o 12428
 
2.3%
p 10625
 
2.0%
Other values (5) 4843
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
S 50448
52.7%
D 16662
 
17.4%
W 15500
 
16.2%
T 10622
 
11.1%
B 1366
 
1.4%
E 1159
 
1.2%
Space Separator
ValueCountFrequency (%)
16659
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 639889
97.5%
Common 16659
 
2.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 117706
18.4%
e 99197
15.5%
r 82200
12.8%
u 50806
7.9%
S 50448
7.9%
a 50047
7.8%
k 49877
7.8%
s 49744
7.8%
D 16662
 
2.6%
n 16659
 
2.6%
Other values (11) 56543
8.8%
Common
ValueCountFrequency (%)
16659
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 656548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 117706
17.9%
e 99197
15.1%
r 82200
12.5%
u 50806
7.7%
S 50448
7.7%
a 50047
7.6%
k 49877
7.6%
s 49744
7.6%
D 16662
 
2.5%
n 16659
 
2.5%
Other values (12) 73202
11.1%

Size
Categorical

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
M
22711 
L
22132 
XL
20876 
XXL
18096 
S
17090 
Other values (6)
28070 

Length

Max length4
Median length3
Mean length1.7941462
Min length1

Characters and Unicode

Total characters231400
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS
2nd row3XL
3rd rowXL
4th rowL
5th row3XL

Common Values

ValueCountFrequency (%)
M 22711
17.6%
L 22132
17.2%
XL 20876
16.2%
XXL 18096
14.0%
S 17090
13.3%
3XL 14816
11.5%
XS 11161
8.7%
6XL 738
 
0.6%
5XL 550
 
0.4%
4XL 427
 
0.3%

Length

2024-03-15T19:43:44.416199image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
m 22711
17.6%
l 22132
17.2%
xl 20876
16.2%
xxl 18096
14.0%
s 17090
13.3%
3xl 14816
11.5%
xs 11161
8.7%
6xl 738
 
0.6%
5xl 550
 
0.4%
4xl 427
 
0.3%

Most occurring characters

ValueCountFrequency (%)
X 84760
36.6%
L 77635
33.6%
S 28251
 
12.2%
M 22711
 
9.8%
3 14816
 
6.4%
e 756
 
0.3%
6 738
 
0.3%
5 550
 
0.2%
4 427
 
0.2%
F 378
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 213735
92.4%
Decimal Number 16531
 
7.1%
Lowercase Letter 1134
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
X 84760
39.7%
L 77635
36.3%
S 28251
 
13.2%
M 22711
 
10.6%
F 378
 
0.2%
Decimal Number
ValueCountFrequency (%)
3 14816
89.6%
6 738
 
4.5%
5 550
 
3.3%
4 427
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 756
66.7%
r 378
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 214869
92.9%
Common 16531
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
X 84760
39.4%
L 77635
36.1%
S 28251
 
13.1%
M 22711
 
10.6%
e 756
 
0.4%
F 378
 
0.2%
r 378
 
0.2%
Common
ValueCountFrequency (%)
3 14816
89.6%
6 738
 
4.5%
5 550
 
3.3%
4 427
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 231400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
X 84760
36.6%
L 77635
33.6%
S 28251
 
12.2%
M 22711
 
9.8%
3 14816
 
6.4%
e 756
 
0.3%
6 738
 
0.3%
5 550
 
0.2%
4 427
 
0.2%
F 378
 
0.2%

ASIN
Text

Distinct7190
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:44.701654image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1289750
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique890 ?
Unique (%)0.7%

Sample

1st rowB09KXVBD7Z
2nd rowB09K3WFS32
3rd rowB07WV4JV4D
4th rowB099NRCT7B
5th rowB098714BZP
ValueCountFrequency (%)
b09sdxffq1 773
 
0.6%
b09sdy8dct 657
 
0.5%
b09sdyq3wg 587
 
0.5%
b081wsckpq 535
 
0.4%
b08xnjg8b1 507
 
0.4%
b09sdxrybg 474
 
0.4%
b08xnj19qh 452
 
0.4%
b081wx4g4q 443
 
0.3%
b09sdy9sq6 431
 
0.3%
b09sdxsq33 395
 
0.3%
Other values (7180) 123721
95.9%
2024-03-15T19:43:45.212589image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 157501
 
12.2%
0 129068
 
10.0%
9 108169
 
8.4%
8 81753
 
6.3%
3 39248
 
3.0%
Y 37669
 
2.9%
X 37593
 
2.9%
K 37458
 
2.9%
Q 35997
 
2.8%
1 35838
 
2.8%
Other values (26) 589456
45.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 749455
58.1%
Decimal Number 540295
41.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 157501
21.0%
Y 37669
 
5.0%
X 37593
 
5.0%
K 37458
 
5.0%
Q 35997
 
4.8%
R 34053
 
4.5%
N 33810
 
4.5%
S 33167
 
4.4%
D 32427
 
4.3%
W 30477
 
4.1%
Other values (16) 279303
37.3%
Decimal Number
ValueCountFrequency (%)
0 129068
23.9%
9 108169
20.0%
8 81753
15.1%
3 39248
 
7.3%
1 35838
 
6.6%
2 34579
 
6.4%
4 33514
 
6.2%
7 31465
 
5.8%
6 24075
 
4.5%
5 22586
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 749455
58.1%
Common 540295
41.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 157501
21.0%
Y 37669
 
5.0%
X 37593
 
5.0%
K 37458
 
5.0%
Q 35997
 
4.8%
R 34053
 
4.5%
N 33810
 
4.5%
S 33167
 
4.4%
D 32427
 
4.3%
W 30477
 
4.1%
Other values (16) 279303
37.3%
Common
ValueCountFrequency (%)
0 129068
23.9%
9 108169
20.0%
8 81753
15.1%
3 39248
 
7.3%
1 35838
 
6.6%
2 34579
 
6.4%
4 33514
 
6.2%
7 31465
 
5.8%
6 24075
 
4.5%
5 22586
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1289750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 157501
 
12.2%
0 129068
 
10.0%
9 108169
 
8.4%
8 81753
 
6.3%
3 39248
 
3.0%
Y 37669
 
2.9%
X 37593
 
2.9%
K 37458
 
2.9%
Q 35997
 
2.8%
1 35838
 
2.8%
Other values (26) 589456
45.7%

Courier Status
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing6872
Missing (%)5.3%
Memory size1007.7 KiB
Shipped
109487 
Unshipped
 
6681
Cancelled
 
5935

Length

Max length9
Median length7
Mean length7.2066452
Min length7

Characters and Unicode

Total characters879953
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowShipped
2nd rowShipped
3rd rowShipped
4th rowShipped
5th rowShipped

Common Values

ValueCountFrequency (%)
Shipped 109487
84.9%
Unshipped 6681
 
5.2%
Cancelled 5935
 
4.6%
(Missing) 6872
 
5.3%

Length

2024-03-15T19:43:45.477055image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:45.677070image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
shipped 109487
89.7%
unshipped 6681
 
5.5%
cancelled 5935
 
4.9%

Most occurring characters

ValueCountFrequency (%)
p 232336
26.4%
e 128038
14.6%
d 122103
13.9%
h 116168
13.2%
i 116168
13.2%
S 109487
12.4%
n 12616
 
1.4%
l 11870
 
1.3%
U 6681
 
0.8%
s 6681
 
0.8%
Other values (3) 17805
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 757850
86.1%
Uppercase Letter 122103
 
13.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 232336
30.7%
e 128038
16.9%
d 122103
16.1%
h 116168
15.3%
i 116168
15.3%
n 12616
 
1.7%
l 11870
 
1.6%
s 6681
 
0.9%
a 5935
 
0.8%
c 5935
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
S 109487
89.7%
U 6681
 
5.5%
C 5935
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 879953
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 232336
26.4%
e 128038
14.6%
d 122103
13.9%
h 116168
13.2%
i 116168
13.2%
S 109487
12.4%
n 12616
 
1.4%
l 11870
 
1.3%
U 6681
 
0.8%
s 6681
 
0.8%
Other values (3) 17805
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 879953
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 232336
26.4%
e 128038
14.6%
d 122103
13.9%
h 116168
13.2%
i 116168
13.2%
S 109487
12.4%
n 12616
 
1.4%
l 11870
 
1.3%
U 6681
 
0.8%
s 6681
 
0.8%
Other values (3) 17805
 
2.0%

Qty
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90443109
Minimum0
Maximum15
Zeros12807
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:45.853940image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.31335359
Coefficient of variation (CV)0.34646485
Kurtosis60.36258
Mean0.90443109
Median Absolute Deviation (MAD)0
Skewness-0.69767777
Sum116649
Variance0.09819047
MonotonicityNot monotonic
2024-03-15T19:43:46.070686image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 115780
89.8%
0 12807
 
9.9%
2 341
 
0.3%
3 32
 
< 0.1%
4 9
 
< 0.1%
5 2
 
< 0.1%
15 1
 
< 0.1%
9 1
 
< 0.1%
13 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 12807
 
9.9%
1 115780
89.8%
2 341
 
0.3%
3 32
 
< 0.1%
4 9
 
< 0.1%
5 2
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
13 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
13 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
5 2
 
< 0.1%
4 9
 
< 0.1%
3 32
 
< 0.1%
2 341
 
0.3%
1 115780
89.8%
0 12807
 
9.9%

currency
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing7795
Missing (%)6.0%
Memory size1007.7 KiB
INR
121180 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters363540
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowINR
2nd rowINR
3rd rowINR
4th rowINR
5th rowINR

Common Values

ValueCountFrequency (%)
INR 121180
94.0%
(Missing) 7795
 
6.0%

Length

2024-03-15T19:43:46.306721image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:46.478313image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
inr 121180
100.0%

Most occurring characters

ValueCountFrequency (%)
I 121180
33.3%
N 121180
33.3%
R 121180
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 363540
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 121180
33.3%
N 121180
33.3%
R 121180
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 363540
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 121180
33.3%
N 121180
33.3%
R 121180
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 363540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 121180
33.3%
N 121180
33.3%
R 121180
33.3%

Amount
Real number (ℝ)

MISSING  ZEROS 

Distinct1410
Distinct (%)1.2%
Missing7795
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean648.56146
Minimum0
Maximum5584
Zeros2343
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:46.665553image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile301
Q1449
median605
Q3788
95-th percentile1176
Maximum5584
Range5584
Interquartile range (IQR)339

Descriptive statistics

Standard deviation281.21169
Coefficient of variation (CV)0.43359296
Kurtosis3.0037534
Mean648.56146
Median Absolute Deviation (MAD)168.81
Skewness0.88548064
Sum78592678
Variance79080.013
MonotonicityNot monotonic
2024-03-15T19:43:46.896403image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
399 5442
 
4.2%
771 2797
 
2.2%
735 2436
 
1.9%
0 2343
 
1.8%
487 2293
 
1.8%
788 1969
 
1.5%
301 1865
 
1.4%
376 1810
 
1.4%
635 1787
 
1.4%
999 1615
 
1.3%
Other values (1400) 96823
75.1%
(Missing) 7795
 
6.0%
ValueCountFrequency (%)
0 2343
1.8%
199 3
 
< 0.1%
218.1 1
 
< 0.1%
229 21
 
< 0.1%
236.19 2
 
< 0.1%
237.14 4
 
< 0.1%
241 4
 
< 0.1%
246.67 7
 
< 0.1%
248 4
 
< 0.1%
249 54
 
< 0.1%
ValueCountFrequency (%)
5584 1
< 0.1%
5495 1
< 0.1%
4235.72 1
< 0.1%
3036 1
< 0.1%
2894 1
< 0.1%
2864 1
< 0.1%
2860 1
< 0.1%
2796 1
< 0.1%
2698 1
< 0.1%
2676 1
< 0.1%
Distinct8955
Distinct (%)6.9%
Missing33
Missing (%)< 0.1%
Memory size1007.7 KiB
2024-03-15T19:43:47.186555image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length50
Median length48
Mean length8.4392905
Min length1

Characters and Unicode

Total characters1088179
Distinct characters82
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4250 ?
Unique (%)3.3%

Sample

1st rowMUMBAI
2nd rowBENGALURU
3rd rowNAVI MUMBAI
4th rowPUDUCHERRY
5th rowCHENNAI
ValueCountFrequency (%)
bengaluru 11944
 
8.1%
hyderabad 9203
 
6.2%
mumbai 8746
 
5.9%
delhi 6899
 
4.7%
new 6706
 
4.5%
chennai 6352
 
4.3%
pune 4723
 
3.2%
kolkata 2911
 
2.0%
noida 2291
 
1.5%
thane 2054
 
1.4%
Other values (6828) 86383
58.3%
2024-03-15T19:43:47.757407image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 158769
 
14.6%
R 70219
 
6.5%
N 69345
 
6.4%
U 68516
 
6.3%
E 60419
 
5.6%
I 56759
 
5.2%
H 50839
 
4.7%
D 50273
 
4.6%
B 44231
 
4.1%
L 41160
 
3.8%
Other values (72) 417649
38.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 908899
83.5%
Lowercase Letter 155080
 
14.3%
Space Separator 19387
 
1.8%
Decimal Number 2170
 
0.2%
Other Punctuation 1859
 
0.2%
Dash Punctuation 280
 
< 0.1%
Open Punctuation 251
 
< 0.1%
Close Punctuation 245
 
< 0.1%
Other Letter 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 31617
20.4%
r 13045
 
8.4%
i 11289
 
7.3%
n 11213
 
7.2%
e 10740
 
6.9%
u 9881
 
6.4%
l 8081
 
5.2%
d 7984
 
5.1%
h 7818
 
5.0%
o 6372
 
4.1%
Other values (17) 37040
23.9%
Uppercase Letter
ValueCountFrequency (%)
A 158769
17.5%
R 70219
 
7.7%
N 69345
 
7.6%
U 68516
 
7.5%
E 60419
 
6.6%
I 56759
 
6.2%
H 50839
 
5.6%
D 50273
 
5.5%
B 44231
 
4.9%
L 41160
 
4.5%
Other values (16) 238369
26.2%
Decimal Number
ValueCountFrequency (%)
0 698
32.2%
1 277
 
12.8%
4 262
 
12.1%
2 208
 
9.6%
6 182
 
8.4%
5 141
 
6.5%
7 116
 
5.3%
3 113
 
5.2%
8 109
 
5.0%
9 64
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 1459
78.5%
. 323
 
17.4%
/ 34
 
1.8%
: 31
 
1.7%
; 7
 
0.4%
' 3
 
0.2%
& 2
 
0.1%
Other Letter
ValueCountFrequency (%)
ल 2
25.0%
ख 2
25.0%
न 2
25.0%
ऊ 2
25.0%
Open Punctuation
ValueCountFrequency (%)
( 248
98.8%
[ 2
 
0.8%
{ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 242
98.8%
] 2
 
0.8%
} 1
 
0.4%
Space Separator
ValueCountFrequency (%)
19387
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1063979
97.8%
Common 24192
 
2.2%
Devanagari 8
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 158769
14.9%
R 70219
 
6.6%
N 69345
 
6.5%
U 68516
 
6.4%
E 60419
 
5.7%
I 56759
 
5.3%
H 50839
 
4.8%
D 50273
 
4.7%
B 44231
 
4.2%
L 41160
 
3.9%
Other values (43) 393449
37.0%
Common
ValueCountFrequency (%)
19387
80.1%
, 1459
 
6.0%
0 698
 
2.9%
. 323
 
1.3%
- 280
 
1.2%
1 277
 
1.1%
4 262
 
1.1%
( 248
 
1.0%
) 242
 
1.0%
2 208
 
0.9%
Other values (15) 808
 
3.3%
Devanagari
ValueCountFrequency (%)
ल 2
25.0%
ख 2
25.0%
न 2
25.0%
ऊ 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1088170
> 99.9%
Devanagari 8
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 158769
 
14.6%
R 70219
 
6.5%
N 69345
 
6.4%
U 68516
 
6.3%
E 60419
 
5.6%
I 56759
 
5.2%
H 50839
 
4.7%
D 50273
 
4.6%
B 44231
 
4.1%
L 41160
 
3.8%
Other values (67) 417640
38.4%
Devanagari
ValueCountFrequency (%)
ल 2
25.0%
ख 2
25.0%
न 2
25.0%
ऊ 2
25.0%
None
ValueCountFrequency (%)
à 1
100.0%
Distinct69
Distinct (%)0.1%
Missing33
Missing (%)< 0.1%
Memory size1007.7 KiB
2024-03-15T19:43:48.042233image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length22
Median length17
Mean length9.533961
Min length2

Characters and Unicode

Total characters1229328
Distinct characters47
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowMAHARASHTRA
2nd rowKARNATAKA
3rd rowMAHARASHTRA
4th rowPUDUCHERRY
5th rowTAMIL NADU
ValueCountFrequency (%)
maharashtra 22260
13.2%
pradesh 19531
11.6%
karnataka 17326
 
10.3%
nadu 11483
 
6.8%
tamil 11483
 
6.8%
telangana 11330
 
6.7%
uttar 10638
 
6.3%
delhi 7048
 
4.2%
kerala 6585
 
3.9%
west 5963
 
3.5%
Other values (45) 44411
26.4%
2024-03-15T19:43:48.585917image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 328824
26.7%
R 120104
 
9.8%
H 100908
 
8.2%
T 97363
 
7.9%
N 76942
 
6.3%
S 57660
 
4.7%
E 56710
 
4.6%
D 52488
 
4.3%
K 45399
 
3.7%
L 43509
 
3.5%
Other values (37) 249421
20.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1159428
94.3%
Space Separator 39373
 
3.2%
Lowercase Letter 29566
 
2.4%
Other Punctuation 961
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 328824
28.4%
R 120104
 
10.4%
H 100908
 
8.7%
T 97363
 
8.4%
N 76942
 
6.6%
S 57660
 
5.0%
E 56710
 
4.9%
D 52488
 
4.5%
K 45399
 
3.9%
L 43509
 
3.8%
Other values (12) 179521
15.5%
Lowercase Letter
ValueCountFrequency (%)
a 9364
31.7%
j 4604
15.6%
r 4560
15.4%
t 4555
15.4%
u 4551
15.4%
h 422
 
1.4%
e 357
 
1.2%
i 344
 
1.2%
l 276
 
0.9%
n 138
 
0.5%
Other values (12) 395
 
1.3%
Other Punctuation
ValueCountFrequency (%)
& 959
99.8%
/ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
39373
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1188994
96.7%
Common 40334
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 328824
27.7%
R 120104
 
10.1%
H 100908
 
8.5%
T 97363
 
8.2%
N 76942
 
6.5%
S 57660
 
4.8%
E 56710
 
4.8%
D 52488
 
4.4%
K 45399
 
3.8%
L 43509
 
3.7%
Other values (34) 209087
17.6%
Common
ValueCountFrequency (%)
39373
97.6%
& 959
 
2.4%
/ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1229328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 328824
26.7%
R 120104
 
9.8%
H 100908
 
8.2%
T 97363
 
7.9%
N 76942
 
6.3%
S 57660
 
4.7%
E 56710
 
4.6%
D 52488
 
4.3%
K 45399
 
3.7%
L 43509
 
3.5%
Other values (37) 249421
20.3%

ship-postal-code
Real number (ℝ)

Distinct9459
Distinct (%)7.3%
Missing33
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean463966.24
Minimum110001
Maximum989898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1007.7 KiB
2024-03-15T19:43:48.841374image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum110001
5-th percentile110092
Q1382421
median500033
Q3600024
95-th percentile769004
Maximum989898
Range879897
Interquartile range (IQR)217603

Descriptive statistics

Standard deviation191476.76
Coefficient of variation (CV)0.41269547
Kurtosis-0.68487475
Mean463966.24
Median Absolute Deviation (MAD)100040
Skewness-0.25833077
Sum5.9824734 × 1010
Variance3.6663352 × 1010
MonotonicityNot monotonic
2024-03-15T19:43:49.100437image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201301 1006
 
0.8%
122001 688
 
0.5%
560037 632
 
0.5%
560068 619
 
0.5%
560076 581
 
0.5%
560043 500
 
0.4%
401107 493
 
0.4%
500072 490
 
0.4%
560100 489
 
0.4%
560066 464
 
0.4%
Other values (9449) 122980
95.4%
ValueCountFrequency (%)
110001 49
< 0.1%
110002 41
 
< 0.1%
110003 65
0.1%
110004 1
 
< 0.1%
110005 70
0.1%
110006 41
 
< 0.1%
110007 52
< 0.1%
110008 86
0.1%
110009 106
0.1%
110010 54
< 0.1%
ValueCountFrequency (%)
989898 1
 
< 0.1%
984196 1
 
< 0.1%
959121 1
 
< 0.1%
855117 2
 
< 0.1%
855116 2
 
< 0.1%
855115 2
 
< 0.1%
855113 9
< 0.1%
855108 2
 
< 0.1%
855107 7
< 0.1%
855102 9
< 0.1%

ship-country
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing33
Missing (%)< 0.1%
Memory size1007.7 KiB
IN
128942 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters257884
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIN
2nd rowIN
3rd rowIN
4th rowIN
5th rowIN

Common Values

ValueCountFrequency (%)
IN 128942
> 99.9%
(Missing) 33
 
< 0.1%

Length

2024-03-15T19:43:49.329177image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:49.491939image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
in 128942
100.0%

Most occurring characters

ValueCountFrequency (%)
I 128942
50.0%
N 128942
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 257884
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 128942
50.0%
N 128942
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 257884
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 128942
50.0%
N 128942
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 257884
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 128942
50.0%
N 128942
50.0%

promotion-ids
Text

MISSING 

Distinct5787
Distinct (%)7.2%
Missing49153
Missing (%)38.1%
Memory size1007.7 KiB
2024-03-15T19:43:49.672655image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length2317
Median length44
Mean length565.96919
Min length25

Characters and Unicode

Total characters45176793
Distinct characters60
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2719 ?
Unique (%)3.4%

Sample

1st rowAmazon PLCC Free-Financing Universal Merchant AAT-WNKTBO3K27EJC,Amazon PLCC Free-Financing Universal Merchant AAT-QX3UCCJESKPA2,Amazon PLCC Free-Financing Universal Merchant AAT-5QQ7BIYYQEDN2,Amazon PLCC Free-Financing Universal Merchant AAT-DSJ2QRXXWXVMQ,Amazon PLCC Free-Financing Universal Merchant AAT-CXJHMC2YJUK76,Amazon PLCC Free-Financing Universal Merchant AAT-CC4FAVTYR4X7C,Amazon PLCC Free-Financing Universal Merchant AAT-XXRCW6NZEPZI4,Amazon PLCC Free-Financing Universal Merchant AAT-CXNSLNBROFDW4,Amazon PLCC Free-Financing Universal Merchant AAT-R7GXNZWISTRFA,Amazon PLCC Free-Financing Universal Merchant AAT-WSJLDN3X7KEMO,Amazon PLCC Free-Financing Universal Merchant AAT-VL6FGQVGQVXUS,Amazon PLCC Free-Financing Universal Merchant AAT-EOKPWFWYW7Y6I,Amazon PLCC Free-Financing Universal Merchant AAT-ZYL5UPUNW6T62,Amazon PLCC Free-Financing Universal Merchant AAT-XVPICCHRWDCAI,Amazon PLCC Free-Financing Universal Merchant AAT-ETXQ3XXWMRXBG,Amazon PLCC Free-Financing Universal Merchant AAT-7X3XCTYG64VBE,Amazon PLCC Free-Financing Universal Merchant AAT-7CHGD3WTS3MHM,Amazon PLCC Free-Financing Universal Merchant AAT-26ZDKNME27X42,Amazon PLCC Free-Financing Universal Merchant AAT-4ZF5KN6E4LJK4,Amazon PLCC Free-Financing Universal Merchant AAT-7RCXIKUAX7DDY,Amazon PLCC Free-Financing Universal Merchant AAT-BRSZZ45H6MHAO,Amazon PLCC Free-Financing Universal Merchant AAT-MKLXOOZWQL7GO,Amazon PLCC Free-Financing Universal Merchant AAT-CB7UNXEXGIJTC,Amazon PLCC Free-Financing Universal Merchant #MP-gzasho-1593152694811,Amazon PLCC Free-Financing Universal Merchant AAT-WLBA4GZ52EAH4
2nd rowIN Core Free Shipping 2015/04/08 23-48-5-108
3rd rowIN Core Free Shipping 2015/04/08 23-48-5-108
4th rowIN Core Free Shipping 2015/04/08 23-48-5-108
5th rowAmazon PLCC Free-Financing Universal Merchant AAT-WNKTBO3K27EJC,Amazon PLCC Free-Financing Universal Merchant AAT-QX3UCCJESKPA2,Amazon PLCC Free-Financing Universal Merchant AAT-5QQ7BIYYQEDN2,Amazon PLCC Free-Financing Universal Merchant AAT-DSJ2QRXXWXVMQ,Amazon PLCC Free-Financing Universal Merchant AAT-CXJHMC2YJUK76,Amazon PLCC Free-Financing Universal Merchant AAT-CC4FAVTYR4X7C,Amazon PLCC Free-Financing Universal Merchant AAT-XXRCW6NZEPZI4,Amazon PLCC Free-Financing Universal Merchant AAT-EOKPWFWYW7Y6I,Amazon PLCC Free-Financing Universal Merchant AAT-ZYL5UPUNW6T62,Amazon PLCC Free-Financing Universal Merchant AAT-ETXQ3XXWMRXBG,Amazon PLCC Free-Financing Universal Merchant AAT-7X3XCTYG64VBE,Amazon PLCC Free-Financing Universal Merchant AAT-7CHGD3WTS3MHM,Amazon PLCC Free-Financing Universal Merchant AAT-26ZDKNME27X42,Amazon PLCC Free-Financing Universal Merchant AAT-4ZF5KN6E4LJK4,Amazon PLCC Free-Financing Universal Merchant AAT-7RCXIKUAX7DDY,Amazon PLCC Free-Financing Universal Merchant AAT-BRSZZ45H6MHAO,Amazon PLCC Free-Financing Universal Merchant AAT-MKLXOOZWQL7GO,Amazon PLCC Free-Financing Universal Merchant AAT-CB7UNXEXGIJTC,Amazon PLCC Free-Financing Universal Merchant #MP-gzasho-1593152694811,Amazon PLCC Free-Financing Universal Merchant AAT-WLBA4GZ52EAH4
ValueCountFrequency (%)
plcc 668899
18.3%
merchant 668899
18.3%
universal 668899
18.3%
free-financing 668899
18.3%
core 46198
 
1.3%
in 46198
 
1.3%
2015/04/08 46198
 
1.3%
shipping 46198
 
1.3%
free 46198
 
1.3%
23-48-5-108 46100
 
1.3%
Other values (343) 705556
19.3%
2024-03-15T19:43:50.163679image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 4072086
 
9.0%
3578420
 
7.9%
e 2815180
 
6.2%
a 2720285
 
6.0%
A 2174776
 
4.8%
i 2111520
 
4.7%
r 2099161
 
4.6%
C 1819658
 
4.0%
F 1534897
 
3.4%
- 1522069
 
3.4%
Other values (50) 20728741
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21612628
47.8%
Uppercase Letter 14886832
33.0%
Space Separator 3578420
 
7.9%
Decimal Number 2803529
 
6.2%
Dash Punctuation 1522069
 
3.4%
Other Punctuation 773315
 
1.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 2174776
14.6%
C 1819658
12.2%
F 1534897
 
10.3%
M 960996
 
6.5%
U 922229
 
6.2%
P 904375
 
6.1%
L 858954
 
5.8%
T 814247
 
5.5%
X 420991
 
2.8%
W 352381
 
2.4%
Other values (16) 4123328
27.7%
Lowercase Letter
ValueCountFrequency (%)
n 4072086
18.8%
e 2815180
13.0%
a 2720285
12.6%
i 2111520
9.8%
r 2099161
9.7%
c 1338754
 
6.2%
o 749439
 
3.5%
h 747359
 
3.5%
g 747359
 
3.5%
s 701195
 
3.2%
Other values (9) 3510290
16.2%
Decimal Number
ValueCountFrequency (%)
2 437707
15.6%
4 398057
14.2%
5 369775
13.2%
7 318570
11.4%
6 284711
10.2%
3 254840
9.1%
1 251026
9.0%
0 210901
7.5%
8 186956
6.7%
9 90986
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 637220
82.4%
/ 92396
 
11.9%
# 43699
 
5.7%
Space Separator
ValueCountFrequency (%)
3578420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1522069
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36499460
80.8%
Common 8677333
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4072086
 
11.2%
e 2815180
 
7.7%
a 2720285
 
7.5%
A 2174776
 
6.0%
i 2111520
 
5.8%
r 2099161
 
5.8%
C 1819658
 
5.0%
F 1534897
 
4.2%
c 1338754
 
3.7%
M 960996
 
2.6%
Other values (35) 14852147
40.7%
Common
ValueCountFrequency (%)
3578420
41.2%
- 1522069
17.5%
, 637220
 
7.3%
2 437707
 
5.0%
4 398057
 
4.6%
5 369775
 
4.3%
7 318570
 
3.7%
6 284711
 
3.3%
3 254840
 
2.9%
1 251026
 
2.9%
Other values (5) 624938
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45176793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 4072086
 
9.0%
3578420
 
7.9%
e 2815180
 
6.2%
a 2720285
 
6.0%
A 2174776
 
4.8%
i 2111520
 
4.7%
r 2099161
 
4.6%
C 1819658
 
4.0%
F 1534897
 
3.4%
- 1522069
 
3.4%
Other values (50) 20728741
45.9%

B2B
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size126.1 KiB
False
128104 
True
 
871
ValueCountFrequency (%)
False 128104
99.3%
True 871
 
0.7%
2024-03-15T19:43:50.372440image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

fulfilled-by
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing89698
Missing (%)69.5%
Memory size1007.7 KiB
Easy Ship
39277 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters353493
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEasy Ship
2nd rowEasy Ship
3rd rowEasy Ship
4th rowEasy Ship
5th rowEasy Ship

Common Values

ValueCountFrequency (%)
Easy Ship 39277
30.5%
(Missing) 89698
69.5%

Length

2024-03-15T19:43:50.543301image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T19:43:50.704222image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
easy 39277
50.0%
ship 39277
50.0%

Most occurring characters

ValueCountFrequency (%)
E 39277
11.1%
a 39277
11.1%
s 39277
11.1%
y 39277
11.1%
39277
11.1%
S 39277
11.1%
h 39277
11.1%
i 39277
11.1%
p 39277
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 235662
66.7%
Uppercase Letter 78554
 
22.2%
Space Separator 39277
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 39277
16.7%
s 39277
16.7%
y 39277
16.7%
h 39277
16.7%
i 39277
16.7%
p 39277
16.7%
Uppercase Letter
ValueCountFrequency (%)
E 39277
50.0%
S 39277
50.0%
Space Separator
ValueCountFrequency (%)
39277
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 314216
88.9%
Common 39277
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 39277
12.5%
a 39277
12.5%
s 39277
12.5%
y 39277
12.5%
S 39277
12.5%
h 39277
12.5%
i 39277
12.5%
p 39277
12.5%
Common
ValueCountFrequency (%)
39277
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 353493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 39277
11.1%
a 39277
11.1%
s 39277
11.1%
y 39277
11.1%
39277
11.1%
S 39277
11.1%
h 39277
11.1%
i 39277
11.1%
p 39277
11.1%

Unnamed: 22
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing49050
Missing (%)38.0%
Memory size1007.7 KiB
False
79925 
(Missing)
49050 
ValueCountFrequency (%)
False 79925
62.0%
(Missing) 49050
38.0%
2024-03-15T19:43:50.849936image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Interactions

2024-03-15T19:43:34.120318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:30.879574image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:32.485891image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:33.271938image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:34.318642image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:31.567566image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:32.688157image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:33.484955image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:34.511402image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:31.962171image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:32.884424image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:33.736079image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:34.698224image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:32.302249image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:33.074925image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-03-15T19:43:33.933257image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Missing values

2024-03-15T19:43:35.078319image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T19:43:35.965097image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

df_indexOrder IDDateStatusFulfilmentSales Channelship-service-levelStyleSKUCategorySizeASINCourier StatusQtycurrencyAmountship-cityship-stateship-postal-codeship-countrypromotion-idsB2Bfulfilled-byUnnamed: 22
00405-8078784-573154504-30-22CancelledMerchantAmazon.inStandardSET389SET389-KR-NP-SSetSB09KXVBD7ZNaN0INR647.62MUMBAIMAHARASHTRA400081.0INNaNFalseEasy ShipNaN
11171-9198151-110114604-30-22Shipped - Delivered to BuyerMerchantAmazon.inStandardJNE3781JNE3781-KR-XXXLkurta3XLB09K3WFS32Shipped1INR406.00BENGALURUKARNATAKA560085.0INAmazon PLCC Free-Financing Universal Merchant AAT-WNKTBO3K27EJC,Amazon PLCC Free-Financing Universal Merchant AAT-QX3UCCJESKPA2,Amazon PLCC Free-Financing Universal Merchant AAT-5QQ7BIYYQEDN2,Amazon PLCC Free-Financing Universal Merchant AAT-DSJ2QRXXWXVMQ,Amazon PLCC Free-Financing Universal Merchant AAT-CXJHMC2YJUK76,Amazon PLCC Free-Financing Universal Merchant AAT-CC4FAVTYR4X7C,Amazon PLCC Free-Financing Universal Merchant AAT-XXRCW6NZEPZI4,Amazon PLCC Free-Financing Universal Merchant AAT-CXNSLNBROFDW4,Amazon PLCC Free-Financing Universal Merchant AAT-R7GXNZWISTRFA,Amazon PLCC Free-Financing Universal Merchant AAT-WSJLDN3X7KEMO,Amazon PLCC Free-Financing Universal Merchant AAT-VL6FGQVGQVXUS,Amazon PLCC Free-Financing Universal Merchant AAT-EOKPWFWYW7Y6I,Amazon PLCC Free-Financing Universal Merchant AAT-ZYL5UPUNW6T62,Amazon PLCC Free-Financing Universal Merchant AAT-XVPICCHRWDCAI,Amazon PLCC Free-Financing Universal Merchant AAT-ETXQ3XXWMRXBG,Amazon PLCC Free-Financing Universal Merchant AAT-7X3XCTYG64VBE,Amazon PLCC Free-Financing Universal Merchant AAT-7CHGD3WTS3MHM,Amazon PLCC Free-Financing Universal Merchant AAT-26ZDKNME27X42,Amazon PLCC Free-Financing Universal Merchant AAT-4ZF5KN6E4LJK4,Amazon PLCC Free-Financing Universal Merchant AAT-7RCXIKUAX7DDY,Amazon PLCC Free-Financing Universal Merchant AAT-BRSZZ45H6MHAO,Amazon PLCC Free-Financing Universal Merchant AAT-MKLXOOZWQL7GO,Amazon PLCC Free-Financing Universal Merchant AAT-CB7UNXEXGIJTC,Amazon PLCC Free-Financing Universal Merchant #MP-gzasho-1593152694811,Amazon PLCC Free-Financing Universal Merchant AAT-WLBA4GZ52EAH4FalseEasy ShipNaN
22404-0687676-727314604-30-22ShippedAmazonAmazon.inExpeditedJNE3371JNE3371-KR-XLkurtaXLB07WV4JV4DShipped1INR329.00NAVI MUMBAIMAHARASHTRA410210.0ININ Core Free Shipping 2015/04/08 23-48-5-108TrueNaNNaN
33403-9615377-813395104-30-22CancelledMerchantAmazon.inStandardJ0341J0341-DR-LWestern DressLB099NRCT7BNaN0INR753.33PUDUCHERRYPUDUCHERRY605008.0INNaNFalseEasy ShipNaN
44407-1069790-724032004-30-22ShippedAmazonAmazon.inExpeditedJNE3671JNE3671-TU-XXXLTop3XLB098714BZPShipped1INR574.00CHENNAITAMIL NADU600073.0INNaNFalseNaNNaN
55404-1490984-457876504-30-22ShippedAmazonAmazon.inExpeditedSET264SET264-KR-NP-XLSetXLB08YN7XDSGShipped1INR824.00GHAZIABADUTTAR PRADESH201102.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNNaN
66408-5748499-685955504-30-22ShippedAmazonAmazon.inExpeditedJ0095J0095-SET-LSetLB08CMHNWBNShipped1INR653.00CHANDIGARHCHANDIGARH160036.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNNaN
77406-7807733-378594504-30-22Shipped - Delivered to BuyerMerchantAmazon.inStandardJNE3405JNE3405-KR-SkurtaSB081WX4G4QShipped1INR399.00HYDERABADTELANGANA500032.0INAmazon PLCC Free-Financing Universal Merchant AAT-WNKTBO3K27EJC,Amazon PLCC Free-Financing Universal Merchant AAT-QX3UCCJESKPA2,Amazon PLCC Free-Financing Universal Merchant AAT-5QQ7BIYYQEDN2,Amazon PLCC Free-Financing Universal Merchant AAT-DSJ2QRXXWXVMQ,Amazon PLCC Free-Financing Universal Merchant AAT-CXJHMC2YJUK76,Amazon PLCC Free-Financing Universal Merchant AAT-CC4FAVTYR4X7C,Amazon PLCC Free-Financing Universal Merchant AAT-XXRCW6NZEPZI4,Amazon PLCC Free-Financing Universal Merchant AAT-EOKPWFWYW7Y6I,Amazon PLCC Free-Financing Universal Merchant AAT-ZYL5UPUNW6T62,Amazon PLCC Free-Financing Universal Merchant AAT-ETXQ3XXWMRXBG,Amazon PLCC Free-Financing Universal Merchant AAT-7X3XCTYG64VBE,Amazon PLCC Free-Financing Universal Merchant AAT-7CHGD3WTS3MHM,Amazon PLCC Free-Financing Universal Merchant AAT-26ZDKNME27X42,Amazon PLCC Free-Financing Universal Merchant AAT-4ZF5KN6E4LJK4,Amazon PLCC Free-Financing Universal Merchant AAT-7RCXIKUAX7DDY,Amazon PLCC Free-Financing Universal Merchant AAT-BRSZZ45H6MHAO,Amazon PLCC Free-Financing Universal Merchant AAT-MKLXOOZWQL7GO,Amazon PLCC Free-Financing Universal Merchant AAT-CB7UNXEXGIJTC,Amazon PLCC Free-Financing Universal Merchant #MP-gzasho-1593152694811,Amazon PLCC Free-Financing Universal Merchant AAT-WLBA4GZ52EAH4FalseEasy ShipNaN
88407-5443024-523316804-30-22CancelledAmazonAmazon.inExpeditedSET200SET200-KR-NP-A-XXXLSet3XLB08L91ZZXNCancelled0NaNNaNHYDERABADTELANGANA500008.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNNaN
99402-4393761-031152004-30-22ShippedAmazonAmazon.inExpeditedJNE3461JNE3461-KR-XXLkurtaXXLB08B3XF5MHShipped1INR363.00ChennaiTAMIL NADU600041.0INNaNFalseNaNNaN
df_indexOrder IDDateStatusFulfilmentSales Channelship-service-levelStyleSKUCategorySizeASINCourier StatusQtycurrencyAmountship-cityship-stateship-postal-codeship-countrypromotion-idsB2Bfulfilled-byUnnamed: 22
128965128965408-5154281-459391205-31-22CancelledAmazonAmazon.inExpeditedJ0119J0119-TP-XXXLTop3XLB08RYPRVPVUnshipped1INR574.0Prayagraj (ALLAHABAD)UTTAR PRADESH211007.0INNaNFalseNaNFalse
128966128966406-9812666-247476105-31-22ShippedAmazonAmazon.inExpeditedSET224SET224-KR-NP-XSSetXSB08MXDBRK1Shipped1INR1132.0CHENNAI 600042TAMIL NADU600042.0INNaNFalseNaNFalse
128967128967404-5182288-165394705-31-22CancelledAmazonAmazon.inExpeditedJNE3638JNE3638-KR-XSkurtaXSB09814Q3QHCancelled0NaNNaNKolkataWEST BENGAL700040.0INNaNFalseNaNFalse
128968128968403-7059995-761872205-31-22ShippedAmazonAmazon.inExpeditedSET264SET264-KR-NP-XLSetXLB08YN7XDSGShipped1INR824.0DelhiDELHI110053.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNFalse
128969128969404-3802633-725076005-31-22CancelledAmazonAmazon.inExpeditedSET044SET044-KR-NP-MSetMB07Q2RTSFBUnshipped1INR612.0MUMBAIMAHARASHTRA400017.0INNaNFalseNaNFalse
128970128970406-6001380-767310705-31-22ShippedAmazonAmazon.inExpeditedJNE3697JNE3697-KR-XLkurtaXLB098112V2VShipped1INR517.0HYDERABADTELANGANA500013.0INNaNFalseNaNFalse
128971128971402-9551604-754431805-31-22ShippedAmazonAmazon.inExpeditedSET401SET401-KR-NP-MSetMB09VC6KHX8Shipped1INR999.0GURUGRAMHARYANA122004.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNFalse
128972128972407-9547469-315235805-31-22ShippedAmazonAmazon.inExpeditedJ0157J0157-DR-XXLWestern DressXXLB0982YZ51BShipped1INR690.0HYDERABADTELANGANA500049.0INNaNFalseNaNFalse
128973128973402-6184140-054595605-31-22ShippedAmazonAmazon.inExpeditedJ0012J0012-SKD-XSSetXSB0894Y2NJQShipped1INR1199.0HalolGujarat389350.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNFalse
128974128974408-7436540-872831205-31-22ShippedAmazonAmazon.inExpeditedJ0003J0003-SET-SSetSB0894X27FCShipped1INR696.0RaipurCHHATTISGARH492014.0ININ Core Free Shipping 2015/04/08 23-48-5-108FalseNaNFalse